%0 Book Section
%T Introduction to NIPS 2017 Competition Track
%A Sergio Escalera
%A Markus Weimer
%A Mikhail Burtsev
%A Valentin Malykh
%A Varvara Logacheva
%A Ryan Lowe
%A Iulian Vlad Serban
%A Yoshua Bengio
%A Alexander Rudnicky
%A Alan W. Black
%A Shrimai Prabhumoye
%A Łukasz Kidzinski
%A Mohanty Sharada
%A Carmichael Ong
%A Jennifer Hicks
%A Sergey Levine
%A Marcel Salathe
%A Scott Delp
%A Iker Huerga
%A Alexander Grigorenko
%A Leifur Thorbergsson
%A Anasuya Das
%A Kyla Nemitz
%A Jenna Sandker
%A Stephen King
%A Alexander S. Ecker
%A Leon A. Gatys
%A Matthias Bethge
%A Jordan Boyd Graber
%A Shi Feng
%A Pedro Rodriguez
%A Mohit Iyyer
%A He He
%A Hal Daume III
%A Sean McGregor
%A Amir Banifatemi
%A Alexey Kurakin
%A Ian Goodfellow
%A Samy Bengio
%E Sergio Escalera
%E Markus Weimer
%B The NIPS ’17 Competition: Building Intelligent Systems
%D 2018
%I Springer
%@ 978-3-319-94042-7
%F Sergio Escalera2018
%O HUPBA; no proj
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=3200), last updated on Thu, 17 Jan 2019 12:44:46 +0100
%X Competitions have become a popular tool in the data science community to solve hard problems, assess the state of the art and spur new research directions. Companies like Kaggle and open source platforms like Codalab connect people with data and a data science problem to those with the skills and means to solve it. Hence, the question arises: What, if anything, could NIPS add to this rich ecosystem?In 2017, we embarked to find out. We attracted 23 potential competitions, of which we selected five to be NIPS 2017 competitions. Our final selection features competitions advancing the state of the art in other sciences such as “Classifying Clinically Actionable Genetic Mutations” and “Learning to Run”. Others, like “The Conversational Intelligence Challenge” and “Adversarial Attacks and Defences” generated new data sets that we expect to impact the progress in their respective communities for years to come. And “Human-Computer Question Answering Competition” showed us just how far we as a field have come in ability and efficiency since the break-through performance of Watson in Jeopardy. Two additional competitions, DeepArt and AI XPRIZE Milestions, were also associated to the NIPS 2017 competition track, whose results are also presented within this chapter.
%U https://link.springer.com/chapter/10.1007%2F978-3-319-94042-7_1
%P 1-23